Bayesian Reflectance Component Separation

  • Ramón Moreno
  • Manuel Graña
  • Alicia d’Anjou
  • Carmen Hernandez
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5712)


We work on a Bayesian approach to the estimation of the specular component of a color image, based on the Dichromatic Reflection Model (DRM). The separation of diffuse and specular components is important for color image segmentation, to allow the segmentation algorithms to work on the best estimation of the reflectance of the scene. In this work we postulate a prior and likelihood energies that model the reflectance estimation process. Minimization of the posterior energy gives the desired reflectance estimation. The approach includes the illumination color normalization and the computation of a specular free image to test the pure diffuse reflection hypothesis.


Random Markov Field Component Separation Color Segmentation Color Image Segmentation Specular Component 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Ramón Moreno
    • 1
  • Manuel Graña
    • 1
  • Alicia d’Anjou
    • 1
  • Carmen Hernandez
    • 1
  1. 1.Grupo de Inteligencia computacionalUniversity of the Basque CountrySpain

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